Existing energy systems are plagued by high variability in demand for power and the lack of effective control over the demand. For example, peak electrical consumption (in terms of wattage) is much higher than average consumption, but the total duration of peak consumption is relatively short. It can be costly to maintain the surge capacity that is only needed during peak consumption periods. As a result, utility companies often impose brown-outs and/or black-outs when capacity is insufficient. This practice has many negative impacts on the residents and businesses in the service area.
Some research has been done in recent years to develop more cost effective and less intrusive methods for easing the strains on existing energy systems. For example, studies have shown that there is a high level of flexibility in actual consumer requirements, and therefore it is possible in theory to reduce peak consumption without depriving consumers of energy they are unwilling to give up.
One conventional approach is to encourage consumers to conserve energy voluntarily by increasing their awareness of energy consumption. For example, studies have shown that information about energy consumption of consumers relative to their neighbors can cause high consumers to dramatically reduce their consumption. Also, studies conducted in California showed that consumers given a “mood ring” that indicates in real time the stress on the power grid dramatically reduced their peak-time consumption.
Another conventional approach is to use energy pricing, either in real or virtual currency, to gauge each consumer's willingness to reduce consumption. In these so-called market-based systems, the price of energy is allowed to fluctuate in real time based on actual demand, which provides an economic incentive for consumers to reduce consumption when the actual demand is high. The rationale behind these systems is that the price a consumer is willing to pay for energy is inversely related to the consumer's willingness to reduce energy consumption, so that a consumer who is more willing to reduce energy consumption will do so at a lower price point compared to another consumer who is less willing to reduce energy consumption. Thus, as the market finds equilibrium, the system approaches a desired state where each consumer reduces energy consumption only to the extent he is willing.
Conventional systems have also been developed to control energy demand related to heating and/or cooling in a building. Typically, these systems employ a centralized architecture where a central controller collects information from various sources and provides control signals to heating and/or cooling units based on the collected information. An example of such a system is illustrated in FIG. 1, which depicts a central controller 110 in communication with sensors and appliances within a home, a consumer 120 living in the home, and a utility provider 130 providing electrical energy to the home. The central controller 110 receives information such as ambient temperature and relative humidity from sensors 140 and 145 placed at various locations. The central controller 110 also receives present consumption information from a heating unit 150 and an air conditioning unit 155 and energy pricing information from the utility provider 130. Then the central controller 110 presents the received information to the consumer 120 and allows the consumer 120 to specify consumption policies, such as different ranges of target temperatures in relation to the pricing of electricity. Based on the current sensed conditions, the current price of electricity and the policies entered by the consumer 120, the central controller 110 sends appropriate control signals to operate the heating unit 150 and the air conditioning unit 155.